An Efficient Data Processing Framework for Mining the Massive Trajectory of Moving Objects
Recently, there has been increasing development of positioning technology, which enables us to collect large scale trajectory data for moving objects. Efficient processing and analysis of massive trajectory data has thus become an emerging and challenging task for both researchers and practitioners. Therefore, in this paper, we propose an efficient data processing framework for mining massive trajectory data. This framework includes three modules: (1) a data distribution module, (2) a data transformation module, and (3) a high performance I/O module. Specifically, we first design a two-step consistent hashing algorithm, which takes into account load balancing, data locality, and scalability, for a data distribution module. In the data transformation module, we present a parallel strategy of a linear referencing algorithm with reduced subtask coupling, easy-implemented parallelization, and low communication cost. Moreover, we propose a compression-aware I/O module to improve the processing efficiency. Finally, we conduct a comprehensive performance evaluation on a synthetic dataset (1.114 TB) and a real world taxi GPS dataset (578 GB). The experimental results demonstrate the advantages of our proposed framework.
Y. Zhou et al., "An Efficient Data Processing Framework for Mining the Massive Trajectory of Moving Objects," Computers, Environment and Urban Systems, vol. 61, pp. 129 - 140, Elsevier, Jan 2017.
The definitive version is available at https://doi.org/10.1016/j.compenvurbsys.2015.03.004
Keywords and Phrases
Data compression; Data handling; Global positioning system; Linear transformations; Mathematical transformations; Metadata; Network management; Taxicabs; Trajectories; Comprehensive performance evaluation; Consistent hashing; Consistent Hashing algorithms; Contribution model; Moving objects; Parallel linear referencing; Parallel strategies; Positioning technologies; Big data; Algorithm; Data mining; Data set; GPS; Trajectory; Compression contribution model; Trajectory of moving object; Two step consistent hashing
International Standard Serial Number (ISSN)
Article - Journal
© 2017 Elsevier, All rights reserved.
01 Jan 2017